Choosing a Problem

Writing an expert system generally involves a great deal of time and money. To avoid costly and emabarrasing failures, people have developed a set of guidelines to determine whether a problem is suitable for an expert system solution:

1. The need for a solution must justify the costs involved in development. There must be a realistic assessment of the costs and benefits involved.
2. Human expertise is not available in all situations where it is needed. If the ``expert'' knowledge is widely available it is unlikely that it will be worth developing an expert system. However, in areas like oil exploration and medicine there may be rare specialised knowledge which could be cheaply provided by an expert system, as and when required, without having to fly in your friendly (but very highly paid) expert.
3. The problem may be solved using symbolic reasoning techniques. It shouldn't require manual dexterity or physical skill.
4. The problem is well structured and does not require (much) common sense knowledge. Common sense knowledge is notoriously hard to capture and represent. It turns out that highly technical fields are easier to deal with, and tend to involve relatively small amounts of well formalised knowledge.
5. The problem cannot be easily solved using more traditional computing methods. If there's a good algorithmic solution to a problem, you don't want to use an expert system.
6. Cooperative and articulate experts exist. For an expert system project to be successful it is essential that the experts are willing to help, and don't feel that their job is threatened! You also need any management and potential users to be involved and have positive attitudes to the whole thing.
7. The problem is of proper size and scope. Typically you need problems that require highly specialized expertise, but would only take a human expert a short time to solve (say an hour, max).

It should be clear that only a small range of problems are appropriate for expert system technology. However, given a suitable problem, expert systems can bring enormous benefits. Systems have been developed, for example, to help analyse samples collected in oil exploration, and to help configure computer systems. Both these systems are (or were) in active use, saving large amounts of money.